This course is designed for data analysts looking to further their analytical capabilities with R. No prior programming experience or statistics knowledge is assumed for this beginner level course.
• Introduction to the R language and the R community
• The RStudio Environment
• Data Types and Structure
• Data Manipulation
• Statistical Summaries and Aggregation
• Data Visualisation
• Introduction to Statistics in R
As with all our courses, attendees are provided with comprehensive training manuals complete with detailed examples and laminated tip sheets for future reference.
Introduction to the R language and the R community
This section will introduce R, its history and the S language and discuss how it is typically used today.
• Introduction to R
• An introduction to the R community
• Online resources (such as R-Help)
• Internal/external support processes
The RStudio Environment
This section will introduce the RStudio Environment and will discuss the way we work in the RStudio environment.
• RStudio
• R Objects
• R Packages
• Scripting
• Help
Data Types and Structure
This section provides a lightweight introduction to common data types in R including dates and times.
• Standard data types in R
• Dates and times
• The “data frame” and “tbl_df”
Data Manipulation
This chapter will focus on reading data in to R, tidying and processing for analysis.
• Importing and Exporting data
• Data manipulation using ‘dplyr’
• Sorting
• Subsetting
• Adding variables
• Data transformation using ‘tidyr’
Statistical Summaries and Aggregation
This sections looks at common R functions for working with columns of data and aggregation using dplyr.
• Simple numerical summaries
• Grouping data
• Aggregation
Graphical Visualisation
This sections looks at the ggplot2 visualisation package.
• Creating a plot
• Titles and Axis labels
• Varying the colour, shape and size by variables
• Working with grouped data
• Faceting (Panelling)
• Working with the legend
Introduction to Statistics in R
This section looks at statistical model fitting in R
• Fitting a simple linear model using an R formula
• Building and comparing models
Pradžios data | Trukmė, d. | Kurso pavadinimas | Kaina, € | Statusas |
Užklausti | 2 | Introduction to R | € 1,000 | |
Užklausti | 2 | Introduction to Analytics with R | € 1,000 |